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Spatial Filtering and Morphological Operation as Pre-Processing Steps in Fingerprint Feature Extraction

Himangkana Goswami, Aditya Bihar Kandali. Published in Image Processing.

Communications on Applied Electronics
Year of Publication: 2015
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Himangkana Goswami, Aditya Bihar Kandali
10.5120/cae2015651749

Himangkana Goswami and Aditya Bihar Kandali. Article: Spatial Filtering and Morphological Operation as Pre-Processing Steps in Fingerprint Feature Extraction. Communications on Applied Electronics 2(5):1-8, July 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Himangkana Goswami and Aditya Bihar Kandali},
	title = {Article: Spatial Filtering and Morphological Operation as Pre-Processing Steps in Fingerprint Feature Extraction},
	journal = {Communications on Applied Electronics},
	year = {2015},
	volume = {2},
	number = {5},
	pages = {1-8},
	month = {July},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Extracting features from a fingerprint image relies mainly on the pre-processing stages the fingerprint has gone through. When the fingerprint image that has been captured is good enough then the final matching stage will produce a satisfying output. But many a times the image which is captured suffers from contact problems such as non-uniform contact, inconsistent contact and irreproducible contact.Because of such adverse and unpredictable image acquisition situations, a biometric system’s (Fingerprint Recognition System) performance suffers from random false rejects/accepts. Hence the need for the pre-processing of an image becomes necessary. In this paper, pre-processing steps of spatial filtering and morphological operation in addition to Gabor filtering are introduced and comparative analyses of the three are done in MATLAB. It has been found that there is a significant removal of false minutiae in the step of minutiae extraction, if spatial or morphological filtering methods are introduced prior to Gabor filtering.

References

  1. Jyoti Rajharia, Dr. P.C Gupta, Arvind Sharma-“Fingerprint-Based Identification System:–A Survey”- International Journal of Computer Technology and Electronics Engineering (IJCTEE) Volume 1, Issue 3
  2. Vipul Awasthi, Vanchha Awasthi,Krishna Kumari Tiwari-“Fingerprint Analysis Using Termination And Bifurcation Minutiae”- -International Journal Of Emerging Technology And Advanced Engineering(IJETAE)-Volume 2,February 2012
  3. Dario Maio and Davide Maltoni-“Direct Gray Scale Minutiae Detection In Fingerprints”-IEEE transactions on Pattern Analysis and Machine Intelligence, Volume 19 No 1, January 1997
  4. Anil Jain, Yi Chen, and Meltem Demirkus-“Pores and Ridges: Fingerprint Matching Using Level 3 Features”-IEEE 2007
  5. Karthik Nandakumar, Anil K. Jain-“Local Correlation-based Fingerprint Matching”- Proceedings of ICVGIP, Kolkata, December 2004
  6. Chul-Hyun Park, Joon-Jae Lee, Mark J. T. Smith, Fellow, IEEE, Sang-il Park, and Kil-Houm Park -“Directional Filter Bank-Based Fingerprint Feature Extraction and Matching”- IEEE Transactions On Circuits And Systems For Video Technology, Vol. 14, No. 1, January 2004
  7. F.A. Afsar, M. Arif and M. Hussain-“Fingerprint Identification and Verification System using Minutiae matching”-National Conference on Emerging Technologies 2004.
  8. Chaohong Wu, Zhixin Shi and VenuGovindaraju.― Fingerprint Image Enhancement Method Using Directional Median Filter.
  9. Yiqiu Dong and ShufangXu. ―A New Directional Weighted Median Filter for Removal of Random Valued Impulse Noise-Signal Processing Letters, IEEE(Volume 14,Issue:3),2007
  10. Dr.E.Chandra-“Noise Elimination In Fingerprint Image Using Median Filter”- Int. J. Advanced Networking and Applications, Volume: 02, Issue: 06, Pages: 950-955 (2011)
  11. Greenberg-“Fingerprint Image Enhancement Using Filtering Techniques”-Pattern Recognition , 2000, proceedings 15th International Conference, Volume 3, page(s)322-325
  12. Roli Bansal, Priti Sehgal & Punam Bedi -“Effective Morphological Extraction of True Fingerprint Minutiae based on the Hit or Miss Transform” International Journal of Biometrics and Bioinformatics(IJBB), Volume (4) : Issue (2)
  13. K.V.Kale, R. R.Manza, V.T.Humbe and Prapti Deshmukh “Fingerprint Image Enhancement Using Morphological Transform” proceedings of GSPx2005 Signal Processing Conference, Santa Clara Conventional Center,California,24-27 October 2005
  14. Lin Hong, Member, IEEE ,Yifei Wan, and Anil Jain “Fingerprint Image Enhancement: Algorithm and Performance Evaluation”,-IEEE Transactions On Pattern Analysis And Machine Intelligence,Vol. 20, 1998
  15. Divya.V-“Adaptive Fingerprint Image Enhancement Based On Spatial Contextual Filtering And Preprocessing Of Data”-IJCAT journal Volume1,Issue 4,2014
  16. P. Maragos & L. Pessoa Morphological Filtering For Image Enhancement And Detection”: Chapter for The Image and Video Processing Handbook
  17. Zhen Ji, Huilian Liao, Xijun Zhang and Q.H. Wu,“Simple and Efficient Soft Morphological Filter in Periodic Noise Reduction”- 2006 IEEE.

Keywords

Fingerprint, minutiae, ridge end, bifurcation, Gabor filtering, spatial filtering, morphological operator